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A Visual Attention-Based Model for Bengali Image Captioning

SN computer science 2023年第2期4卷 208页

作者： Das, Bidyut Pal, Ratnabali Majumder, Mukta Phadikar, Santanu Sekh, Arif Ahmed Department of Information Technology Haldia Institute of Technology West Bengal Haldia 721657 India Department of Applied Mathematics NIT Durgapur West Bengal Durgapur 713213 India Department of Computational Science Brainware University West Bengal Kolkata 700125 India Department of Computer Science and Technology University of North Bengal West Bengal Siliguri 734014 India Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology W.B. West Bengal Haringhata 741249 India School of Computer Science and Engineering XIM University Odisha Bhubaneswar 752050 India

Image caption or description generation is a fundamental task that involves computer vision (CV) and natural language processing (NLP) ideas to recognize an image-context and produces description(s) using a natural language. Bengali is one of the world’s most commonly spoken languages, ranking fifth. For this reason, large research achievements have been recognized to image captioning, i.e. explaining images with grammatically correct and semantically meaningful Bengali sentences. Many established datasets exist for image caption generation in English, but no standard dataset is available for Bengali. This paper proposes a model for generating automatic image captions in the Bengali language. This study uses only two initial available Bengali datasets to train the encoder-decoder neural network model. We have curated the human errors available in the datasets and benchmarked. Experimental results of this proposed model performs better than other baseline models using these datasets. It achieved 0.67 and 0.65 BLEU-1, and 0.26 and 0.24 BLEU-4 respectively. We expect that our research will take attentions to more researchers from regional language understanding and accelerate Bengali vision-language understanding. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Attention mechanism Bengali image caption Bengali NLP Deep learning Image description

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Fictitious null spaces for improving the solution of injective inverse problems

arXiv

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arXiv 2024年

作者： Elvetun, Ole Løseth Knudsen, Kim Nielsen, Bjørn Fredrik Faculty of Science and Technology Norwegian University of Life Sciences Norway Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark

For linear ill-posed problems with nontrivial null spaces, Tikhonov regularization and truncated singular value decomposition (TSVD) typically yield solutions that are close to the minimum norm solution. Such a bias is not always desirable, and we have therefore in a series of papers developed a weighting procedure which produces solutions with a different and controlled bias. This methodology can also conveniently be invoked when sparsity regularization is employed. The purpose of the present work is to study the potential use of this weighting applied to injective operators. The image under a compact operator of the singular vectors/functions associated with very small singular values will be almost zero. Consequently, one may regard these singular vectors/functions to constitute a basis for a fictitious null space that allows us to mimic the previous weighting procedure. It turns out that this regularization by weighting can improve the solution of injective inverse problems compared with more traditional approaches. We present some analysis of this methodology and exemplify it numerically, using sparsity regularization, for three PDE-driven inverse problems: the inverse heat conduction problem, the Cauchy problem for Laplace’s equation, and the (linearized) Electrical Impedance Tomography problem with experimental data. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

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Optimizing Reliability in Total Artificial Heart Design Through Redundancy Strategies and Swarm-Inspired Optimization

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International Journal of applied and Computational mathematics 2023年第6期9卷 1-20页

作者： Bhandari, Ashok Singh Rawat, Suhani Sharma, Yashaswi Ram, Mangey Kumar, Akshay Department of Mathematics School of Basic and Applied Sciences Shri Guru Ram Rai University Uttarakhand Dehradun India Department of Mathematics Graphic Era Hill University Uttarakhand Dehradun India Department of Mathematics Computer Science and Engineering Graphic Era (Deemed to be University) Dehardun India Institute of Advanced Manufacturing Technologies Peter the Great St. Petersburg Polytechnic University Saint Petersburg 195251 Russian Federation

With noticeable advancements in medical technology, the seemingly impossible procedures have now come to practical implementation. Artificial Heart is one such device which is developed to replace ineffectual human hearts in order to provide a better quality of life for heart failure patients, making it crucial to hold high reliability. In the proposed work, the TAH is considered for the reliability redundancy allocation problem with an objective of maximizing system reliability. The non-linear mixed integer programming problem is solved by using the recently developed meta-heuristic—whale optimization algorithm. A comparative study is presented for optimized reliability of the system using active and cold standby redundancy strategies. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Active redundancy Artificial heart Cold-standby redundancy Reliability redundancy allocation problem Whale optimization algorithm

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Radiative peristaltic transport of Ree-Eyring fluid through porous medium in asymmetric channel subjected to combined effect of inclined MHD and convective conditions

Radiative peristaltic transport of Ree-Eyring fluid through ...

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2020 Ibn Al-Haitham International Conference for Pure and applied sciences, IHICPS 2020

作者： Ali, Hayat A. Department of Applied Science Mathematics and Application of Computer University of Technology Baghdad Iraq

This study emphasizes the flow phenomenon of trapped bolus traveling along the interior walls of asymmetric inclined channels contains a non-Newtonian Ree-Eyring. The flow was exposed to influenced by inclined MHD field, thermal heat radiative, and porous media. Further, no slip and convective thermal conditions are considered. Mathematical expression for governing equations are reformulated and in accordance with lubrication approximations, nonlinear partial differential equations of the flow reduced into a system of ordinary differential equations associated with boundary conditions an approximate solution is deduced by implementing perturbation strategy for tiny A Ree-Eyring fluid parameter. Finally, a graphical description is presented to figure out the elevation behavior of flow quantities i.e. velocity profile, temperature distribution, pressure rise, and streamlines formulation due to variation of emerging involved parameters. The study analyzed that the velocity profile reveals mixed behavior via increment of Ree-Eyring parameters η, A as well as Hartman number H and Darcy number Da. whereas the thermal radiative parameter Rn accelerates the temperature distribution profile. The study calculations are made by the "Mathematica 11.3"package. © Published under licence by IOP Publishing Ltd.

关键词： Temperature distribution

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A Fitness Movement Evaluation System Using Deep Learning 15

A Fitness Movement Evaluation System Using Deep Learning

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15th International Conference on Knowledge and Systems Engineering, KSE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Hao-Wei Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

ISBN: (纸本)9798350329742

This paper proposes a fitness movement evaluation system using deep learning. The system uses a deep convolutional neural network (CNN) to extract features from pictures of fitness movements. The features are then used to classify the movements into different categories. The system is evaluated on a dataset of pictures of fitness movements. The results show that the system can accurately classify the movements into different categories. The system is designed to provide feedback to users on their fitness movements. The proposed system is a valuable tool for fitness enthusiasts. The main contribution of this paper is to propose a way to give users a score for their fitness movement. It can help users improve their fitness and track their progress over time. The system is also a valuable tool for fitness professionals. It can help professionals develop new fitness programs and provide feedback to their clients. © 2023 IEEE.

关键词： Convolutional neural networks

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A Collaborators Recommendation Method Based on Multi-feature Fusion 1

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3rd International Conference on Neural Computing for Advanced Applications, NCAA 2022

作者： Yuan, Qi Shao, Lujiao Zhang, Xinyu Yu, Xinrui Sun, Huiyue Ma, Jianghong Meng, Weizhi Gao, Xiao-Zhi Zhang, Haijun Departmant of Computer Science Harbin Institudte of Technology Shenzhen China Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark School of Computing University of Eastern Finland Kuopio Finland

ISBN: (数字)9789811961427

ISBN: (纸本)9789811961410

This research introduces a new collaborators recommendation model based on multi-feature fusion. Specifically, we use a tree structure to integrate scholar information and extract content features from a scholar tree by using a Tree2vector-CLE model. Then, from the heterogeneous academic network, we extract the meta-path feature between scholars, which quantifies the similarity and co-operation potential between scholars from a multidimensional perspective. By combining content and meta-path features, we reconstruct a co-authorship network. Finally, we use the network representation learning method to represent the nodes in the reconstructed co-authorship network where the top-k collaborators are recommended for the target scholar with the random walk strategy controlled by the meta-path feature weighting. Experimental results on a real dataset demonstrate that our proposed method is effective in the task of collaborators recommendation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning systems

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An Application-Aware Clustering Strategy in Vehicular Ad Hoc Network 6

An Application-Aware Clustering Strategy in Vehicular Ad Hoc...

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6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

作者： Wei, Chi-Hung Chang, Chin-Chih Chu, Chien-Hao Hsiao, Sean Chung Hua University Ph.D. Program in Engineering Science Hsinchu City Taiwan Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Chung Hua University Bachelor Program in Applied Foreign Language and Smart Commerce Hsinchu City Taiwan

ISBN: (纸本)9798350340921

VANET (Vehicular Ad Hoc Network) was developed to address the unique challenges of communication in a mobile vehicular environment. This technology can enhance driving safety and traffic control. Moreover, similar principles can be applied to unmanned aerial vehicles and robotics. When transmitting data in moving vehicles, it is challenging as access points and base stations keep changing, requiring handovers between different access points and base stations. Clustering is a popular approach used to address this challenge. Common clustering strategies are based on the proximity, communication range, the density, the application requirements of the moving vehicles, or hybrid of them. In this paper, we propose a clustering strategy based on the application sublayer in the vehicle communication protocol. If two computing devices on the move run the same application, they can be grouped together. The contribution of this research is to develop a clustering mechanism based on the application with very low overhead. We also validate the proposed method through simulations. The simulation results indicate that the proposed method is feasible. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Enhanced prairie dog optimization with Levy flight and dynamic opposition-based learning for global optimization and engineering design problems

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Neural Computing and Applications 2024年第19期36卷 11137-11170页

作者： Biswas, Saptadeep Shaikh, Azharuddin Ezugwu, Absalom El-Shamir Greeff, Japie Mirjalili, Seyedali Bera, Uttam Kumar Abualigah, Laith Department of Mathematics National Institute of Technology Agartala Tripura Agartala India Unit for Data Science and Computing North-West University 11 Hoffman Street Potchefstroom2520 South Africa Faculty of Natural and Agricultural Sciences School of Computer Science and Information Systems North-West University Vanderbijlpark South Africa Centre for Artificial Intelligence Research and Optimization Torrens University Australia Fortitude Valley BrisbaneQLD4006 Australia Research Center University of Tabuk Tabuk71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia College of Engineering Yuan Ze University Taoyuan32003 Taiwan MEU Research Unit Middle East University Amman11831 Jordan

This study proposes a new prairie dog optimization algorithm version called EPDO. This new version aims to address the issues of premature convergence and slow convergence that were observed in the original PDO algorithm. To improve performance, several modifications are introduced in EPDO. First, a dynamic opposite learning strategy is employed to increase the diversity of the population and prevent premature convergence. This strategy helps the algorithm avoid falling into local optima and promotes global optimization. Additionally, the Lévy dynamic random walk technique is utilized in EPDO. This modified Lévy flight with random walk reduces the algorithm’s running time for the test function’s ideal value, accelerating its convergence. The proposed approach is evaluated using 33 benchmark problems from CEC 2017 and compared against seven other comparative techniques: GWO, MFO, ALO, WOA, DA, SCA, and RSA. Numerical results demonstrate that EPDO produces good outcomes and performs well in solving benchmark problems. To further validate the results and assess reliability, the authors employ average rank tests, the measurement of alternatives, and ranking according to the compromise solution (MARCOS) method, as well as a convergence report of EPDO and other algorithms. Furthermore, the effectiveness of the EPDO algorithm is demonstrated by applying it to five design problems. The results indicate that EPDO achieves impressive outcomes and proves its capability to address practical issues. The algorithm performs well in solving benchmark and practical design problems, as supported by the numerical results and validation methods used in the study. © The Author(s) 2024.

关键词： Global optimization

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Adapted Metrics for a Modified Coulomb/Newton’s Potential

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Journal of High Energy Physics, Gravitation and Cosmology 2023年第4期9卷 1311-1355页

作者： Lucian M. Ionescu Cristina-Liliana Pripoae Gabriel Pripoae Department of Mathematics Illinois State University Normal IL USA Department of Applied Mathematics The Bucharest University of Economic Studies Bucharest Romania Faculty of Mathematics and Computer Science University of Bucharest Bucharest Romania

Modified Theories of Gravity include spin dependence in General Relativity, to account for additional sources of gravity instead of dark matter/energy approach. The spin-spin interaction is already included in the effective nuclear force potential, and theoretical considerations and experimental evidence hint to the hypothesis that Gravity originates from such an interaction, under an averaging process over spin directions. This invites to continue the line of theory initiated by Einstein and Cartan, based on tetrads and spin effects modeled by connections with torsion. As a first step in this direction, the article considers a new modified Coulomb/Newton Law accounting for the spin-spin interaction. The physical potential is geometrized through specific affine connections and specific semi-Riemannian metrics, canonically associated to it, acting on a manifold or at the level of its tangent bundle. Freely falling particles in these “toy Universes” are determined, showing an interesting behavior and unexpected patterns.

关键词： Modified Gravity Theory Spin Coulomb’s Law Newton’s Law Modified Coulomb’s Law Nuclear Force Adapted Connection Adapted Metric

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Searching with Opponent-Awareness

Searching with Opponent-Awareness

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Adaptive and Learning Agents Workshop, ALA 2021 at AAMAS 2021

作者： Phan, Timy Department of Computer Science and Mathematics Munich University of Applied Sciences Munich Germany

We propose Searching with Opponent-Awareness (SOA), an approach to leverage opponent-aware planning without explicit or a priori opponent models for improving performance and social welfare in multi-agent systems. To this end, we develop an opponent-aware MCTS scheme using multi-armed bandits based on Learning with Opponent-Learning Awareness (LOLA) and compare its effectiveness with other bandits, including UCB1. Our evaluations include several different settings and show the benefits of SOA are especially evident with increasing number of agents. © 2021 Association for Computing Machinery.

关键词： Multi agent systems

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